Acute sleep deprivation upregulates serotonin 2A receptors in the frontal cortex of mice via the immediate early gene Egr3.

Serotonin 2A receptors (5-HT2ARs) mediate the hallucinogenic effects of psychedelic drugs and are a key target of the leading class of medications used to treat psychotic disorders. These findings suggest that dysfunction of 5-HT2ARs may contribute to the symptoms of schizophrenia, a mental illness characterized by perceptual and cognitive disturbances. Indeed, numerous studies have found that 5-HT2ARs are reduced in the brains of individuals with schizophrenia. However, the mechanisms that regulate 5-HT2AR expression remain poorly understood. Here, we show that a physiologic environmental stimulus, sleep deprivation, significantly upregulates 5-HT2AR levels in the mouse frontal cortex in as little as 6-8 h (for mRNA and protein, respectively). This induction requires the activity-dependent immediate early gene transcription factor early growth response 3 (Egr3) as it does not occur in Egr3 deficient (-/-) mice. Using chromatin immunoprecipitation, we show that EGR3 protein binds to the promoter of Htr2a, the gene that encodes the 5-HT2AR, in the frontal cortex in vivo, and drives expression of in vitro reporter constructs via two EGR3 binding sites in the Htr2a promoter. These results suggest that EGR3 directly regulates Htr2a expression, and 5-HT2AR levels, in the frontal cortex in response to physiologic stimuli. Analysis of publicly available post-mortem gene expression data revealed that both EGR3 and HTR2A mRNA are reduced in the prefrontal cortex of schizophrenia patients compared to controls. Together these findings suggest a mechanism by which environmental stimuli alter levels of a brain receptor that may mediate the symptoms, and treatment, of mental illness.

Decreased Femoral Trochlear Length Associated With Increased Anterior Knee Pain Following Total Knee Arthroplasty: A New Anatomical Perspective.

BACKGROUND: Anterior knee pain (AKP) and patello-femoral crepitus (PFCr) continue to plague total knee arthroplasty patients despite advances and modifications to implant design and surgical techniques. We present our study of the femoral trochlear length measurement preimplantation and postimplantation and its association with AKP/PFCr and clinical scores. METHODS: Using computer navigation, we obtained several measurements in 263 total knee arthroplasty (posterior-stabilized) patients, which included femoral native trochlear measurement (NTM) and difference in trochlear length between implant and native trochlea. We report their association with Knee Society Score, Western Ontario McMaster University Arthritic Index, and AKP/PFCr at 1 year postoperatively. RESULTS: Mean Knee Society Score and Western Ontario McMaster University Arthritic Index scores were significantly worse in patients who had AKP (P = .005 and P = .002 respectively). Receiver operating characteristic curve showed a statistically significant association between NTM and AKP (Area under the curve = 0.609, P = .014). Lower the NTM, greater was the incidence of AKP. Analysis of the receiver operating characteristic curve identified the cutoff value of NTM to be ≤25.5 with sensitivity of 76.7(95% confidence interval - 57.7 - 90.1) and specificity of 46.9 (95% confidence interval - 41.9 - 55.1). Patients who had NTM of ≤25.5 had an odds ratio of 3.09 to have AKP. The difference in trochlear length ranged from 7.4 to 32.1 millimeters, indicating that postimplantation there was lengthwise overstuffing along the trochlea in every patient. CONCLUSION: We found that the shorter the native femoral trochlea and greater the difference between implanted and native trochlea, the higher was the occurrence of AKP. A mismatch in trochlear measurement preimplantation and postimplantation resulted in lengthwise overstuffing in the anterior knee causing AKP and PFCr.

Using E. coli population to predict foodborne pathogens in pastured poultry farms.

Escherichia coli shows the potential of indicating foodborne pathogens. The purpose of this study is to investigate the association between E. coli and foodborne pathogens such as Campylobacter, Salmonella, and Listeria in pastured poultry farms, as well as in related processing facilities. Five different sample types: (i) feces, (ii) soil, (iii) whole carcass rinse during processing (WCR-P), (iv) whole carcass rinse of final product after chilling and storage (WCR-F), and (v) ceca were measured for E. coli populations. A logistic regression model for pathogen presence was developed for each sample type. The E. coli population significantly increased the predicted probability of Salmonella presence for soil and WCR-P samples (p = 0.0011 and p = 0.0157 respectively). For Campylobacter, the initial prevalence in feces and ceca were high and a decreasing trend of detecting Campylobacter was observed as E. coli concentration increased. In soil and WCR-P models, the probability of the presence of Campylobacter significantly increased as E. coli population increased. These models provide a practical and effective way of evaluating the relationship between E. coli and foodborne pathogens and enable prediction of foodborne pathogen presence based on E. coli prevalence within the pastured poultry farm-to-fork continuum.

Factors that predict Listeria prevalence in distribution centers handling fresh produce.

Listeria species prevalence has been investigated at nearly all stages of the fresh produce supply chain; however, it has not been examined in transportation and distribution center (DC) related environments. Between December 2019 and March 2021, 18 DCs handling fresh produce were environmentally sampled for Listeria. Swab samples were collected from a variety of surfaces (e.g., floors, pallets, forklifts) in several areas of each DC (e.g., cold storage, shipping and receiving docks). Impaction air samples, relative humidity, and temperature data were also collected. While no Listeria spp. were isolated from air samples (n = 170), they were isolated from 49 of 982 (ca. 5%) environmental samples. The proportion of Listeria spp. positive samples varied significantly across individual DCs (P < 0.01). Several facility characteristics were significantly associated with a Listeria spp. positive sample, such as zone, sampling site dryness, and cleaning regimen. A random forest model (sensitivity: 0.786, specificity: 0.874) identified geographical location and general sampling location (e.g., cold storage rooms, shipping docks) as the two most important variables associated with Listeria spp. detection. This study identified likely harborage sites (e.g., floors, cleaning equipment) of Listeria spp. in DCs across the US and emphasized the importance of sanitation operations in Listeria-prone areas.

Antibiotic Resistance Influences Growth Rates and Cross-Tolerance to Lactic Acid in Escherichia coli O157:H7 H1730.

Escherichia coli O157:H7-contaminated beef has been implicated in numerous foodborne outbreaks. Contamination occurs despite the use of antimicrobial interventions such as lactic acid (LA). In addition, resistance to antibiotics such as ampicillin and streptomycin among isolates has been frequently reported. The influence of antibiotic resistance (ABR) on growth rates and cross-tolerance of lettuce isolate E. coli O157:H7 H1730 to LA was evaluated. Antibiotic-resistant strain variants were generated by conferring resistance to either ampicillin (ampC) or streptomycin (strepC) or both ampicillin and streptomycin (ampC strepC) through incremental exposure to the antibiotics. Ampicillin resistance was also conferred by plasmid transformation to generate the ampP and ampP strepC strains. The minimum inhibitory concentration of LA on all the strains evaluated was 0.375% v/v. The lag phase duration of all strains except E. coli O157:H7 ampP strepC increased with increasing concentration of LA. The ampP strepC and ampC strains were most tolerant to 5% LA with declines in the cell population of 2.86 and 2.56 log CFU/mL, respectively (p < 0.05). The ampP strepC strain was the most tolerant when evaluated by the live/dead viability assay. The addition of the efflux pump inhibitor, carbonyl cyanide m-chlorophenylhydrazone, with 2.5% LA resulted in a significant increase in sensitivity in the no resistance (NR) wild-type and ampC strains, resulting in 6.62 and 6.65 log CFU/mL reduction, respectively, while the highly tolerant ampP strepC strain had a 2.90 log CFU/mL decrease. Tolerance to LA was significantly influenced by both the ABR profile of the strain and LA concentration. The results from this study indicate that E. coli O157:H7 strains with certain ABR profiles might be more tolerant to LA.

Does Postoperative Intravenous Ferric Carboxymaltose Hasten the Recovery of Hemoglobin in Patients Post Total Knee Arthroplasty?

BACKGROUND: Timely and effective iron supplementation may help reduce the incidence of postoperative anemia and its associated problems. In this study, we aim to assess the efficacy of intravenous ferric carboxy maltose (FCM) on improving hemoglobin(Hb) level posttotal knee arthroplasty (TKA). METHODS: We retrospectively reviewed 263 patients who had undergone unilateral TKA with 157 patients in the study group (year 2019) and 106 in the control group (year 2016). Patients in the study group received FCM (500 mg IV) on postoperative day 1, whereas patients in the control group did not receive FCM or any other iron supplementation postoperatively. Hb levels were recorded preoperatively (Pr-Hb), postoperatively on day 3 (Day3-Hb) and postoperatively at 5(+1) weeks (Week5-Hb). Statistical analysis was performed using student's paired and unpaired t-tests. RESULTS: Pr-Hb and Day3-Hb levels were comparable in the control and study group, while Week5-Hb levels were significantly higher (P < .001) in the study group. The drop in Hb at Day3 from preoperative values was comparable between the two groups (P = 1.0). The rise in Hb from Day3 to 5 weeks was significantly higher in the study group as compared to the control group (P < .001). The difference between Pr-Hb and Week5-Hb was significantly lower (P < .001) in the study group compared to the control group. However, Week5-Hb in both groups remained lower than Pr-Hb (P < .001) in all patients. CONCLUSION: Intravenous FCM (500 mg) was found to be a safe method of iron supplementation to improve hemoglobin levels rapidly and consistently, post-TKA. We need to further study the additive effect of higher dose FCM (1000 mg) on hemoglobin recovery.

ECG Data Analysis with Denoising Approach and Customized CNNs.

In the last decade, the proactive diagnosis of diseases with artificial intelligence and its aligned technologies has been an exciting and fruitful area. One of the areas in medical care where constant monitoring is required is cardiovascular diseases. Arrhythmia, one of the cardiovascular diseases, is generally diagnosed by doctors using Electrocardiography (ECG), which records the heart's rhythm and electrical activity. The use of neural networks has been extensively adopted to identify abnormalities in the last few years. It is found that the probability of detecting arrhythmia increases if the denoised signal is used rather than the raw input signal. This paper compares six filters implemented on ECG signals to improve classification accuracy. Custom convolutional neural networks (CCNNs) are designed to filter ECG data. Extensive experiments are drawn by considering the six ECG filters and the proposed custom CCNN models. Comparative analysis reveals that the proposed models outperform the competitive models in various performance metrics.

A predictive growth model for Clostridium botulinum during cooling of cooked uncured ground beef.

A dynamic model to predict the germination and outgrowth of Clostridium botulinum spores in cooked ground beef was presented. Raw ground beef was inoculated with a ten-strain C. botulinum spore cocktail to achieve approximately 2 log spores/g. The inoculated ground beef was vacuum packaged, cooked to 71 °C to heat shock the spores, cooled to below 10 °C, and incubated isothermally at temperatures from 10 to 46 °C. C. botulinum growth was quantified and fitted into the primary Baranyi Model. Secondary models were fitted to maximum specific growth rate and lag phase duration using Modified Ratkowsky equation (R2 0.96) and hyperbolic function (R2 0.94), respectively. Similar experiments were also performed under non-isothermal (cooling) conditions. Acceptable zone prediction (APZ) analysis was conducted on growth data collected over 3 linear cooling regimes from the current study. The model performance (prediction errors) for all 22 validation data points collected in the current work were within the APZ limits (-1.0 to +0.5 log CFU/g). Additionally, two other growth data sets of C. botulinum reported in the literature were also subjected to the APZ analysis. In these validations, 20/22 and 10/14 predictions fell within the APZ limits. The model presented in this work can be employed to predict C. botulinum spore germination and growth in cooked uncured beef under non-isothermal conditions. The beef industry processors and food service organizations can utilize this predictive microbial model for cooling deviations and temperature abused situations and in developing customized process schedules for cooked, uncured beef products.

A System Model for Understanding the Role of Animal Feces as a Route of Contamination of Leafy Greens before Harvest.

The majority of foodborne outbreaks in the United States associated with the consumption of leafy greens contaminated with Escherichia coli O157:H7 have been reported during the period of July to November. A dynamic system model consisting of subsystems and inputs to the system (soil, irrigation, cattle, wild pig, and rainfall) simulating a hypothetical farm was developed. The model assumed two crops of lettuce in a year and simulated planting, irrigation, harvesting, ground preparation for the new crop, contamination of soil and plants, and survival of E. coli O157:H7. As predicted by the baseline model for crops harvested in different months from conventional fields, an estimated 13 out of 257 (5.05%) first crops harvested in July would have at least one plant with at least 1 CFU of E. coli O157:H7. Predictions indicate that no first crops would be contaminated with at least 1 CFU of E. coli O157:H7 for other months (April to June). The maximum E. coli O157:H7 concentration in a plant was higher in the second crop (27.10 CFU) than in the first crop (9.82 CFU). For the second crop, the probabilities of having at least one plant with at least 1 CFU of E. coli O157:H7 in a crop were predicted as 15/228 (6.6%), 5/333 (1.5%), 14/324 (4.3%), and 6/115 (5.2%) in August, September, October, and November, respectively. For organic fields, the probabilities of having at least one plant with ≥1 CFU of E. coli O157:H7 in a crop (3.45%) were predicted to be higher than those for the conventional fields (2.15%). IMPORTANCE: This study is the first attempt toward developing a mathematical system model to understand the pathway of E. coli O157:H7 in the production of leafy greens. Results of the presented system model indicate that the seasonality of outbreaks of E. coli O157:H7-associated contamination of leafy greens was in good agreement with the prevalence of this pathogen in cattle and wild pig feces in a major leafy greens-producing region in California. On the basis of comparisons among the results of different scenarios, it can be recommended that the concentration of E. coli O157:H7 in leafy greens can be reduced considerably if contamination of soil with wild pig and cattle feces is mitigated.

Modeling the long-term kinetics of Salmonella survival on dry pet food.

Due to multiple outbreaks and large-scale product recalls, Salmonella has emerged as a priority pathogen in dry pet food and treats. However, little data are available to quantify risks posed by these classes of products to both pets and their owners. Specifically, the kinetics of Salmonella survival on complex pet food matrices are not available. This study measured the long-term kinetics of Salmonella survival on a dry pet food under storage conditions commonly encountered during production, retail, and in households (aw < 0.60, 23 °C). A Salmonella enterica cocktail of 12 strains isolated from dry pet foods and treats was used to inoculate commercial dry dog food. Salmonella was enumerated on non-selective (BHI) and selective (XLD and BS) media. Results at 570 days indicated an initial relatively rapid decline (up to 54 days), followed by a much slower extended decline phase. The Weibull model provided a satisfactory fit for time series of Log-transformed Salmonella counts from all three media (δ: mean 4.65 day/Log (CFU/g); p: mean 0.364 on BHI). This study provides a survival model that can be applied in quantitative risk assessment models.

Development of Dose-Response Models to Predict the Relationship for Human Toxoplasma gondii Infection Associated with Meat Consumption.

Toxoplasma gondii is a protozoan parasite that is responsible for approximately 24% of deaths attributed to foodborne pathogens in the United States. It is thought that a substantial portion of human T. gondii infections is acquired through the consumption of meats. The dose-response relationship for human exposures to T. gondii-infected meat is unknown because no human data are available. The goal of this study was to develop and validate dose-response models based on animal studies, and to compute scaling factors so that animal-derived models can predict T. gondii infection in humans. Relevant studies in literature were collected and appropriate studies were selected based on animal species, stage, genotype of T. gondii, and route of infection. Data were pooled and fitted to four sigmoidal-shaped mathematical models, and model parameters were estimated using maximum likelihood estimation. Data from a mouse study were selected to develop the dose-response relationship. Exponential and beta-Poisson models, which predicted similar responses, were selected as reasonable dose-response models based on their simplicity, biological plausibility, and goodness fit. A confidence interval of the parameter was determined by constructing 10,000 bootstrap samples. Scaling factors were computed by matching the predicted infection cases with the epidemiological data. Mouse-derived models were validated against data for the dose-infection relationship in rats. A human dose-response model was developed as P (d) = 1-exp (-0.0015 × 0.005 × d) or P (d) = 1-(1 + d × 0.003 / 582.414)(-1.479) . Both models predict the human response after consuming T. gondii-infected meats, and provide an enhanced risk characterization in a quantitative microbial risk assessment model for this pathogen.

A Systematic Meta-Analysis of Toxoplasma gondii Prevalence in Food Animals in the United States.

Toxoplasma gondii is a widely distributed protozoan parasite. The Centers for Disease Control and Prevention reported that T. gondii is one of three pathogens (along with Salmonella and Listeria), that together account for >70% of all deaths due to foodborne illness in the United States. Food animals are reservoirs for T. gondii and act as one of the sources for parasite transmission to humans. Based on limited population-based data, the Food and Agriculture Organization/World Health Organization estimated that approximately 22% of human T. gondii infections are meatborne. The objective of the current study was to conduct a systematic meta-analysis to provide a precise estimation of T. gondii infection prevalence in food animals produced in the United States. Four databases were searched to collect eligible studies. Prevalence was estimated in six animal categories (confinement-raised market pigs, confinement-raised sows, non-confinement-raised pigs, lamb, goats, and non-confinement-raised chickens) by a quality-effects model. A wide variation in prevalence was observed in each animal category. Animals raised outdoors or that have outdoor access had a higher prevalence as compared with animals raised indoors. T. gondii prevalence in non-confinement-raised pigs ranked the highest (31.0%) followed by goats (30.7%), non-confinement-raised chickens (24.1%), lambs (22.0%), confinement-raised sows (16.7%), and confinement-raised market pigs (5.6%). These results indicate that T. gondii-infected animals are a food safety concern. The computed prevalence can be used as an important input in quantitative microbial risk assessment models to further predict public health burden.

Interventions to reduce Salmonella and Campylobacter during chilling and post-chilling stages of poultry processing: a systematic review and meta-analysis.

Salmonella and Campylobacter are common bacterial hazards causing foodborne illnesses worldwide. A large proportion of Salmonella and Campylobacter illnesses are attributed to contaminated poultry products that are mishandled or under cooked. Processing interventions such as chilling and post-chill dip are critical to reducing microbial contamination of poultry. A comprehensive search of the literature published between 2000 and 2021 was conducted in the databases Web of Science, Academic Search Complete, and Academic OneFile. Studies were included if they were in English and investigated the effects of interventions against Salmonella and/or Campylobacter on whole carcasses and/or parts during the chilling or post-chill stages of poultry processing. Random-effects meta-analyses were performed using the "meta" package in the R programming language. Subgroup analyses were assessed according to outcome measure reported, microorganism tested, processing stage assessed, and chemical treatment used. The results included 41 eligible studies. Eighteen studies reported results of 28 separate interventions against Salmonella and 31 reported results of 50 separate interventions against Campylobacter. No significant difference (P> 0.05) was observed when comparing the combined mean difference of all interventions targeting Salmonella to the combined mean difference of all interventions targeting Campylobacter or when comparing chilling times within each pathogen subgroup. For analyses examining antimicrobial additives, peroxyacetic acid (PAA) had the largest reduction against Salmonella population regardless of chilling time (P< 0.05). PAA also had the largest reduction against Campylobacter population and prevalence during primary chilling (P< 0.01). Air chilling showed a lower reduction for Campylobacter than any immersion chilling intervention (P< 0.05). Chilling time and antimicrobial used during poultry processing had varying effects depending on the pathogen and outcome measure investigated (concentration or prevalence). High heterogeneity and low sample numbers in most analyses suggest that more high-quality research that is well-designed and has transparent reporting of methodology and results is needed to corroborate the results.

Antibiotic resistance associated lactic acid cross tolerance in Shiga-toxin producing E. coli.

Introduction: The occurrence of antibiotic resistant (ABR) bacteria in foods is a growing public health challenge. We evaluated sanitizer cross-tolerance among ABR Escherichia coli (E. coli) O157:H7 and non-O157:H7 Shiga-toxin producing E. coli (STEC) serogroups. Sanitizer tolerance in STEC could be a public health concern as mitigation strategies against the pathogen might be compromised. Methods: Resistance to ampicillin and streptomycin were evolved in E. coli serogroups: O157:H7 (H1730, and ATCC 43895), O121:H19 and O26:H11. Resistance to antibiotics was evolved chromosomally through incremental exposure to ampicillin (amp C) and streptomycin (strep C). Transformation using a plasmid was performed to confer resistance to ampicillin to generate amp P strep C. Results: The minimum inhibitory concentration (MIC) of lactic acid for all strains evaluated was 0.375% v/v. Analysis of bacterial growth parameters in tryptic soy broth amended with 0.0625% v/v, 0.125% v/v, and 0.25% v/v (subMIC) lactic acid indicated that growth correlated positively with the lag phase duration, and negatively with both the maximum growth rate and change in population density for all strains evaluated except for the highly tolerant variant- O157:H7 amp P strep C. Strains O121 NR (non-ABR), O121 amp C, O121 amp P strep C, O157:H7 H1730 amp C and O157:H7 H1730 amp P strep C were not inactivated after exposure to 1% and 2.5% v/v lactic acid for 300 s. No recovery of cells was observed after the strains were exposed to 5% v/v lactic acid for 300 s. ABR strains O157:H7 H1730 amp C and O157: H7 H1730 amp P strep C demonstrated a high tolerance to lactic acid (P ≤ 0.05). Conclusion: ABR in isolate E. coli O157: H7 H1730 may improve tolerance to lactic acid. Increased tolerance may be discerned by evaluating growth parameters of bacteria in presence of sub-MIC levels of lactic acid.

Universal hydrolysis probe-based approach for specific detection and genotyping of foodborne pathogens.

Real-time PCR assays are the method of choice for the specific detection of DNA targets. Multiple real-time PCR chemistries are used for developing pathogen detection assays. Among them, a hydrolysis probe is a preferred choice for pathogen detection assays. Two known limitations of hydrolysis probes are high cost and limited storage life. Therefore, this study aimed to develop and validate a universal hydrolysis probe (UHP)-based approach with high-resolution melt (HRM) analysis capabilities. The approach can be used for the detection and genotyping of target DNA. The approach described in this study was validated by standardizing nine UHP assays for detecting seven Shiga toxin-producing Escherichia coli serogroups, Listeria monocytogenes, and Salmonella strains. These nine assays were validated with 141 pure culture bacterial strains. Additionally, the HRM capability of the developed approach was validated for three UHP assays targeting E. coli O26, O111, and O121 using 96 DNAs isolated from enriched food samples. The nine assays specifically detected the target bacterial strains, and the three assays showed single nucleotide polymorphism (SNP) identification capability and no cross-reactivity with non-target strains. The developed approach can be performed in singleplex or multiplex format and combined with HRM analysis. The data from this study demonstrate that the UHP real-time PCR approach is a robust method for detecting any deoxyribonucleic acid target.

Assessing the Risk of Seasonal Effects of Campylobacter Contaminated Broiler Meat Prepared In-Home in the United States.

Campylobacter has consistently posed a food safety issue in broiler meat. This study aimed to create a quantitative microbial risk assessment model from retail to consumption, designed to evaluate the seasonal risk of campylobacteriosis associated with broiler meat consumption in the United States. To achieve this, data was gathered to build distributions that would enable us to predict the growth of Campylobacter during various stages such as retail storage, transit, and home storage. The model also included potential fluctuations in concentration during food preparation and potential cross-contamination scenarios. A Monte Carlo simulation with 100,000 iterations was used to estimate the risk of infection per serving and the number of infections in the United States by season. In the summer, chicken meat was estimated to have a median risk of infection per serving of 9.22 × 10-7 and cause an average of about 27,058,680 infections. During the winter months, the median risk of infection per serving was estimated to be 4.06 × 10-7 and cause an average of about 12,085,638 infections. The risk assessment model provides information about the risk of broiler meat to public health by season. These results will help understand the most important steps to reduce the food safety risks from contaminated chicken products.

Relationship of the Poultry Microbiome to Pathogen Colonization, Farm Management, Poultry Production, and Foodborne Illness Risk Assessment.

Despite the continuous progress in food science and technology, the global burden of foodborne illnesses remains substantial, with pathogens in food causing millions of infections each year. Traditional microbiological culture methods are inadequate in detecting the full spectrum of these microorganisms, highlighting the need for more comprehensive detection strategies. This review paper aims to elucidate the relationship between foodborne pathogen colonization and the composition of the poultry microbiome, and how this knowledge can be used for improved food safety. Our review highlights that the relationship between pathogen colonization varies across different sections of the poultry microbiome. Further, our review suggests that the microbiome profile of poultry litter, farm soil, and farm dust may serve as potential indicators of the farm environment's food safety issues. We also agree that the microbiome of processed chicken samples may reveal potential pathogen contamination and food quality issues. In addition, utilizing predictive modeling techniques on the collected microbiome data, we suggest establishing correlations between particular taxonomic groups and the colonization of pathogens, thus providing insights into food safety, and offering a comprehensive overview of the microbial community. In conclusion, this review underscores the potential of microbiome analysis as a powerful tool in food safety, pathogen detection, and risk assessment.

Impact of chlorine or peracetic acid on inactivation of Salmonella, Escherichia coli, and Listeria monocytogenes in agricultural water.

Preharvest agricultural water has been recognized as one of the routes of contamination for foodborne pathogens during fruit and vegetable production. Several strategies have been proposed to reduce the risk of pathogens, including preharvest water chemigation, but literature is lacking with regards to microbiological inactivation of common bacterial foodborne pathogens associated with fresh produce contamination, Salmonella enterica, Shiga-toxigenic Escherichia coli (STEC), and Listeria monocytogenes, in surface irrigation water after exposure to chlorine and peracetic acid (PAA). Surface water supplied by a local irrigation district was collected over the summer of 2019. Water was autoclaved, divided into 100 mL samples, and inoculated with a cocktail of five Salmonella, STEC, or Listeria monocytogenes strains or a single strain non-pathogenic E. coli. Samples were then treated with 3, 5, or 7 ppm of free chlorine or PAA, and surviving populations were evaluated using a time-kill assay. A first-order kinetic model was used to fit the inactivation data and obtain the D-values. A secondary model was used to explain the changes due to the type of water, treatment, and microorganism. At a concentration of 3 ppm, the observed and predicted D-values of free chlorine treatments were higher than that of PAA treatments for ground and surface water. Results indicated that PAA was more effective inactivating bacteria than sodium hypochlorite at concentrations of 3 and 5 ppm for both water sources (surface and ground). However, at 7 ppm, the effectiveness of PAA and sodium hypochlorite showed no statistically significant difference for both surface and groundwater. Findings will provide information regarding efficacy of chemical sanitizers like chlorine and PAA for inactivation of Salmonella, Listeria, and STEC in surface water from which treatments can be derived. Ultimately benefitting growers in the selection of an appropriate method for in-field treatment of irrigation water if deemed necessary.

Influence of antibiotic-resistance and exudate on peroxyacetic acid tolerance in O157 and non-O157 Shiga toxin producing E. coli.

Shiga toxin producing Escherichia coli (STEC) continues to cause foodborne outbreaks associated with beef and beef products despite consistent use of antimicrobial interventions. In this study, the influence of antibiotic resistance (ABR) in E. coli O157:H7 H1730, O157:H7 43,895, O121:H19 and O26:H11 on tolerance to peroxyacetic acid (PAA) was evaluated. Further, bactericidal concentrations of PAA in the presence of nutrient rich media (Tryptic Soy Broth, TSB and beef exudates) and nutrient deficient media (Sterile Deionized Water, SDW and Phosphate Buffered Saline, PBS) were evaluated for all bacterial strains. Antibiotic resistance to ampicillin (amp C), or ampicillin and streptomycin (amp P strep C) was generated in each bacterial strain through incremental exposure to the antibiotics or by plasmid transformation (n = 12 total strains). The mean bactericidal concentrations of PAA were higher (p ≤ 0.05) in nutrient rich media (205.55 ± 31.11 in beef exudate and 195.83 ± 25.00 ppm in TSB) than in nutrient deficient media (57.91 ± 11.97 ppm in SDW and 56.66 ± 9.56 ppm in PBS). Strain O157: H7 ampP strepC was the most tolerant to PAA (p ≤ 0.05). At 200 ppm in nutrient rich media and 60 ppm in nutrient deficient media, all bacterial strains declined in population to below the limit of detection. Analysis of the beef exudates indicated the presence of diverse amino acids that have been associated with acid tolerance. The results from this study indicate that beef exudates could contribute to acid tolerance and suggest that some STEC bacterial strains with certain ABR profiles might be more tolerant to PAA.

Changes in chemical characteristics and modeling sensory parameters of stored pecan nutmeats.

Pecan is a major specialty crop produced in the United States. Sensory evaluation and chemical analyses of pecan nutmeats are integral components of shelf life and have been employed to investigate changes during storage, but there remains a lack of knowledge regarding storage stability. Specifically, the association between shelf life and chemical characteristics has not been investigated. We aimed to investigate the chemical changes in pecan nuts during a range of storage treatments (temperature, relative humidity, packaging material, and modified atmosphere). The results of the chemical analyses were used to build a volatile compound-based sensory prediction model. The work has utility as a rapid method to measure lipid oxidation in pecan, which is of value to the pecan industry. The research also determined a possible association between pecan nut volatile compounds and sensory attributes of pecans, and their perception by human subjects. Building a sensory-based prediction model would reduce dependency on expensive and time-consuming sensory methods.